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ISMB
1998
13 years 8 months ago
A Hidden Markov Model for Predicting Transmembrane Helices in Protein Sequences
A novel method to model and predict the location and orientation of alpha helices in membrane- spanning proteins is presented. It is based on a hidden Markov model (HMM) with an a...
Erik L. L. Sonnhammer, Gunnar von Heijne, Anders K...
ICC
2009
IEEE
123views Communications» more  ICC 2009»
14 years 2 months ago
Combining Hidden Markov Models for Improved Anomaly Detection
—In host-based intrusion detection systems (HIDS), anomaly detection involves monitoring for significant deviations from normal system behavior. Hidden Markov Models (HMMs) have...
Wael Khreich, Eric Granger, Robert Sabourin, Ali M...
MOBIHOC
2010
ACM
13 years 5 months ago
Fine-grained mobility characterization: steady and transient state behaviors
Recent popularization of personal hand-held mobile devices makes it important to characterize the mobility pattern of mobile device users, so as to accurately predict user mobilit...
Wei Gao, Guohong Cao
DATAMINE
2006
83views more  DATAMINE 2006»
13 years 7 months ago
Structural Hidden Markov Models Using a Relation of Equivalence: Application to Automotive Designs
Standard hidden Markov models (HMM's) have been studied extensively in the last two decades. It is well known that these models assume state conditional independence of the ob...
Djamel Bouchaffra, Jun Tan
FLAIRS
2008
13 years 9 months ago
Learning Dynamic Naive Bayesian Classifiers
Hidden Markov models are a powerful technique to model and classify temporal sequences, such as in speech and gesture recognition. However, defining these models is still an art: ...
Miriam Martínez, Luis Enrique Sucar